234 lines
8.2 KiB
Python
234 lines
8.2 KiB
Python
from unittest.mock import Mock, patch, PropertyMock
|
|
|
|
import pytest
|
|
|
|
from mem0.vector_stores.baidu import BaiduDB, OutputData
|
|
from pymochow.model.enum import MetricType, TableState, ServerErrCode
|
|
from pymochow.model.schema import Field, Schema, VectorIndex, FilteringIndex, HNSWParams, AutoBuildRowCountIncrement
|
|
from pymochow.model.table import Partition, Row, VectorSearchConfig, VectorTopkSearchRequest, FloatVector, Table
|
|
from pymochow.exception import ServerError
|
|
|
|
|
|
@pytest.fixture
|
|
def mock_mochow_client():
|
|
with patch("pymochow.MochowClient") as mock_client:
|
|
yield mock_client
|
|
|
|
|
|
@pytest.fixture
|
|
def mock_configuration():
|
|
with patch("pymochow.configuration.Configuration") as mock_config:
|
|
yield mock_config
|
|
|
|
|
|
@pytest.fixture
|
|
def mock_bce_credentials():
|
|
with patch("pymochow.auth.bce_credentials.BceCredentials") as mock_creds:
|
|
yield mock_creds
|
|
|
|
|
|
@pytest.fixture
|
|
def mock_table():
|
|
mock_table = Mock(spec=Table)
|
|
# 设置 Table 类的属性
|
|
type(mock_table).database_name = PropertyMock(return_value="test_db")
|
|
type(mock_table).table_name = PropertyMock(return_value="test_table")
|
|
type(mock_table).schema = PropertyMock(return_value=Mock())
|
|
type(mock_table).replication = PropertyMock(return_value=1)
|
|
type(mock_table).partition = PropertyMock(return_value=Mock())
|
|
type(mock_table).enable_dynamic_field = PropertyMock(return_value=False)
|
|
type(mock_table).description = PropertyMock(return_value="")
|
|
type(mock_table).create_time = PropertyMock(return_value="")
|
|
type(mock_table).state = PropertyMock(return_value=TableState.NORMAL)
|
|
type(mock_table).aliases = PropertyMock(return_value=[])
|
|
return mock_table
|
|
|
|
|
|
@pytest.fixture
|
|
def mochow_instance(mock_mochow_client, mock_configuration, mock_bce_credentials, mock_table):
|
|
mock_database = Mock()
|
|
mock_client_instance = Mock()
|
|
|
|
# Mock the client creation
|
|
mock_mochow_client.return_value = mock_client_instance
|
|
|
|
# Mock database operations
|
|
mock_client_instance.list_databases.return_value = []
|
|
mock_client_instance.create_database.return_value = mock_database
|
|
mock_client_instance.database.return_value = mock_database
|
|
|
|
# Mock table operations
|
|
mock_database.list_table.return_value = []
|
|
mock_database.create_table.return_value = mock_table
|
|
mock_database.describe_table.return_value = Mock(state=TableState.NORMAL)
|
|
mock_database.table.return_value = mock_table
|
|
|
|
return BaiduDB(
|
|
endpoint="http://localhost:8287",
|
|
account="test_account",
|
|
api_key="test_api_key",
|
|
database_name="test_db",
|
|
table_name="test_table",
|
|
embedding_model_dims=128,
|
|
metric_type="COSINE",
|
|
)
|
|
|
|
|
|
def test_insert(mochow_instance, mock_mochow_client):
|
|
vectors = [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]
|
|
payloads = [{"name": "vector1"}, {"name": "vector2"}]
|
|
ids = ["id1", "id2"]
|
|
|
|
mochow_instance.insert(vectors=vectors, payloads=payloads, ids=ids)
|
|
|
|
# Verify table.upsert was called with correct data
|
|
assert mochow_instance._table.upsert.call_count == 2
|
|
calls = mochow_instance._table.upsert.call_args_list
|
|
|
|
# Check first call
|
|
first_row = calls[0][1]["rows"][0]
|
|
assert first_row._data["id"] == "id1"
|
|
assert first_row._data["vector"] == [0.1, 0.2, 0.3]
|
|
assert first_row._data["metadata"] == {"name": "vector1"}
|
|
|
|
# Check second call
|
|
second_row = calls[1][1]["rows"][0]
|
|
assert second_row._data["id"] == "id2"
|
|
assert second_row._data["vector"] == [0.4, 0.5, 0.6]
|
|
assert second_row._data["metadata"] == {"name": "vector2"}
|
|
|
|
|
|
def test_search(mochow_instance, mock_mochow_client):
|
|
# Mock search results
|
|
mock_search_results = Mock()
|
|
mock_search_results.rows = [
|
|
{"row": {"id": "id1", "metadata": {"name": "vector1"}}, "score": 0.1},
|
|
{"row": {"id": "id2", "metadata": {"name": "vector2"}}, "score": 0.2},
|
|
]
|
|
mochow_instance._table.vector_search.return_value = mock_search_results
|
|
|
|
vectors = [0.1, 0.2, 0.3]
|
|
results = mochow_instance.search(query="test", vectors=vectors, limit=2)
|
|
|
|
# Verify search was called with correct parameters
|
|
mochow_instance._table.vector_search.assert_called_once()
|
|
call_args = mochow_instance._table.vector_search.call_args
|
|
request = call_args[0][0] if call_args[0] else call_args[1]["request"]
|
|
|
|
assert isinstance(request, VectorTopkSearchRequest)
|
|
assert request._vector_field == "vector"
|
|
assert isinstance(request._vector, FloatVector)
|
|
assert request._vector._floats == vectors
|
|
assert request._limit == 2
|
|
assert isinstance(request._config, VectorSearchConfig)
|
|
assert request._config._ef == 200
|
|
|
|
# Verify results
|
|
assert len(results) == 2
|
|
assert results[0].id == "id1"
|
|
assert results[0].score == 0.1
|
|
assert results[0].payload == {"name": "vector1"}
|
|
assert results[1].id == "id2"
|
|
assert results[1].score == 0.2
|
|
assert results[1].payload == {"name": "vector2"}
|
|
|
|
|
|
def test_search_with_filters(mochow_instance, mock_mochow_client):
|
|
mochow_instance._table.vector_search.return_value = Mock(rows=[])
|
|
|
|
vectors = [0.1, 0.2, 0.3]
|
|
filters = {"user_id": "user123", "agent_id": "agent456"}
|
|
|
|
mochow_instance.search(query="test", vectors=vectors, limit=2, filters=filters)
|
|
|
|
# Verify search was called with filter
|
|
call_args = mochow_instance._table.vector_search.call_args
|
|
request = call_args[0][0] if call_args[0] else call_args[1]["request"]
|
|
|
|
assert request._filter == 'metadata["user_id"] = "user123" AND metadata["agent_id"] = "agent456"'
|
|
|
|
|
|
def test_delete(mochow_instance, mock_mochow_client):
|
|
vector_id = "id1"
|
|
mochow_instance.delete(vector_id=vector_id)
|
|
|
|
mochow_instance._table.delete.assert_called_once_with(primary_key={"id": vector_id})
|
|
|
|
|
|
def test_update(mochow_instance, mock_mochow_client):
|
|
vector_id = "id1"
|
|
new_vector = [0.7, 0.8, 0.9]
|
|
new_payload = {"name": "updated_vector"}
|
|
|
|
mochow_instance.update(vector_id=vector_id, vector=new_vector, payload=new_payload)
|
|
|
|
mochow_instance._table.upsert.assert_called_once()
|
|
call_args = mochow_instance._table.upsert.call_args
|
|
row = call_args[0][0] if call_args[0] else call_args[1]["rows"][0]
|
|
|
|
assert row._data["id"] == vector_id
|
|
assert row._data["vector"] == new_vector
|
|
assert row._data["metadata"] == new_payload
|
|
|
|
|
|
def test_get(mochow_instance, mock_mochow_client):
|
|
# Mock query result
|
|
mock_result = Mock()
|
|
mock_result.row = {"id": "id1", "metadata": {"name": "vector1"}}
|
|
mochow_instance._table.query.return_value = mock_result
|
|
|
|
result = mochow_instance.get(vector_id="id1")
|
|
|
|
mochow_instance._table.query.assert_called_once_with(primary_key={"id": "id1"}, projections=["id", "metadata"])
|
|
|
|
assert result.id == "id1"
|
|
assert result.score is None
|
|
assert result.payload == {"name": "vector1"}
|
|
|
|
|
|
def test_list(mochow_instance, mock_mochow_client):
|
|
# Mock select result
|
|
mock_result = Mock()
|
|
mock_result.rows = [{"id": "id1", "metadata": {"name": "vector1"}}, {"id": "id2", "metadata": {"name": "vector2"}}]
|
|
mochow_instance._table.select.return_value = mock_result
|
|
|
|
results = mochow_instance.list(limit=2)
|
|
|
|
mochow_instance._table.select.assert_called_once_with(filter=None, projections=["id", "metadata"], limit=2)
|
|
|
|
assert len(results[0]) == 2
|
|
assert results[0][0].id == "id1"
|
|
assert results[0][1].id == "id2"
|
|
|
|
|
|
def test_list_cols(mochow_instance, mock_mochow_client):
|
|
# Mock table list
|
|
mock_tables = [
|
|
Mock(spec=Table, database_name="test_db", table_name="table1"),
|
|
Mock(spec=Table, database_name="test_db", table_name="table2"),
|
|
]
|
|
mochow_instance._database.list_table.return_value = mock_tables
|
|
|
|
result = mochow_instance.list_cols()
|
|
|
|
assert result == ["table1", "table2"]
|
|
|
|
|
|
def test_delete_col_not_exists(mochow_instance, mock_mochow_client):
|
|
# 使用正确的 ServerErrCode 枚举值
|
|
mochow_instance._database.drop_table.side_effect = ServerError(
|
|
"Table not exists", code=ServerErrCode.TABLE_NOT_EXIST
|
|
)
|
|
|
|
# Should not raise exception
|
|
mochow_instance.delete_col()
|
|
|
|
|
|
def test_col_info(mochow_instance, mock_mochow_client):
|
|
mock_table_info = {"table_name": "test_table", "fields": []}
|
|
mochow_instance._table.stats.return_value = mock_table_info
|
|
|
|
result = mochow_instance.col_info()
|
|
|
|
assert result == mock_table_info
|